Construction of an immunogenic cell death-related LncRNA signature to predict the prognosis of patients with lung adenocarcinoma.

IF 2.1 4区 医学 Q3 GENETICS & HEREDITY BMC Medical Genomics Pub Date : 2024-11-27 DOI:10.1186/s12920-024-02042-y
Shuaishuai Wang, Yi Zhang
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Abstract

Background: Lung adenocarcinoma (LUAD) is one of the most common malignant diseases worldwide. This study aimed to construct an immunogenic cell death (ICD)-related long non-coding RNA (lncRNA) signature to effectively predict the prognosis of LUAD.

Methods: The RNA-sequencing and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA). Least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox proportional hazard regression analysis were utilized to construct lncRNA signature. Then, the reliability of the signature was evaluated in the training, validation and whole cohorts. The differences in the immune landscape and drug sensitivity between the low- and high-risk groups were analyzed. Finally, the expression level of the selected ICD-related lncRNAs in LUAD cell lines via reverse transcription quantitative PCR (RT-qPCR). CCK-8 and transwell assays were performed to study biological function of AC245014.3.

Results: A signature consisting of 5 ICD-related lncRNAs was constructed. Kaplan Meier (K-M) survival analysis showed shorter overall survival (OS) in high-risk group. The receiver operating characteristic (ROC) curves and Multivariate Cox regression analysis showed the signature was good predictive and independent prognostic factor in LUAD. Moreover, the high-risk group had a lower level of antitumor immunity and was less sensitive to some chemotherapeutics and targeted drugs. Finally, the expression level of selected ICD-related lncRNAs was validated in LUAD cell lines by RT-qPCR. Knockdown of AC245014.3 significantly suppressed LUAD proliferation, migration and invasion.

Conclusions: In this study, an ICD-related lncRNA signature was constructed, which could accurately predict the prognosis of LUAD patients and guide clinical treatment.

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构建免疫原性细胞死亡相关 LncRNA 标志,预测肺腺癌患者的预后。
背景:肺腺癌(LUAD)是全球最常见的恶性肿瘤之一:肺腺癌(LUAD)是全球最常见的恶性疾病之一。本研究旨在构建与免疫原性细胞死亡(ICD)相关的长非编码RNA(lncRNA)特征,以有效预测LUAD的预后:方法:从癌症基因组图谱(TCGA)中下载LUAD的RNA测序和临床数据。利用最小绝对收缩和选择算子(LASSO)和逐步多变量Cox比例危险回归分析构建lncRNA特征。然后,在训练队列、验证队列和整个队列中评估了特征的可靠性。分析了低风险组和高风险组在免疫景观和药物敏感性方面的差异。最后,通过反转录定量 PCR(RT-qPCR)分析了所选 ICD 相关 lncRNA 在 LUAD 细胞系中的表达水平。此外,还进行了 CCK-8 和 transwell 试验,以研究 AC245014.3 的生物学功能:结果:构建了由 5 个 ICD 相关 lncRNA 组成的特征。Kaplan Meier(K-M)生存分析显示,高风险组的总生存期(OS)较短。接受者操作特征曲线(ROC)和多变量 Cox 回归分析表明,该特征对 LUAD 具有良好的预测性和独立的预后因素。此外,高危组的抗肿瘤免疫水平较低,对一些化疗药物和靶向药物的敏感性也较低。最后,通过 RT-qPCR 验证了所选 ICD 相关 lncRNA 在 LUAD 细胞系中的表达水平。敲除AC245014.3可显著抑制LUAD的增殖、迁移和侵袭:本研究构建了ICD相关lncRNA特征,可准确预测LUAD患者的预后并指导临床治疗。
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来源期刊
BMC Medical Genomics
BMC Medical Genomics 医学-遗传学
CiteScore
3.90
自引率
0.00%
发文量
243
审稿时长
3.5 months
期刊介绍: BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.
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